Effect of Intestinal Flora on Protein Expression of Drug-Metabolizing

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Effect of intestinal flora on protein expression of drug-metabolizing enzymes and transporters in liver and kidney of germ-free and antibiotics-treated mice Takuya Kuno, Mio Hirayama-Kurogi, Shingo Ito, and Sumio Ohtsuki Mol. Pharmaceutics, Just Accepted Manuscript • DOI: 10.1021/acs.molpharmaceut.6b00259 • Publication Date (Web): 05 Jul 2016 Downloaded from http://pubs.acs.org on July 15, 2016

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Molecular Pharmaceutics

Effect of intestinal flora on protein expression of drug-metabolizing enzymes and transporters in liver and kidney of germ-free and antibiotics-treated mice Takuya Kuno†,♯, Mio Hirayama-Kurogi†,‡,§, Shingo Ito†,‡,§, and Sumio Ohtsuki*†,‡,§ †

Department of Pharmaceutical Microbiology, Graduate School of Pharmaceutical Sciences,

Kumamoto University ♯

Department of Drug Metabolism and Pharmacokinetics, Drug Safety Research Center,

Tokushima Research Institute, Otsuka Pharmaceutical Co., Ltd. ‡

Department of Pharmaceutical Microbiology, Faculty of Life Sciences, Kumamoto University

§

AMED-CREST, Japan Agency for Medical Research and Development, 1-7-1 Otemachi,

Chiyoda, Tokyo 100-0004, Japan

1 ACS Paragon Plus Environment


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ABSTRACT

Dysbiosis (alteration of intestinal flora) is associated with various host physiologies, including diseases. The purpose of this study was to clarify the effect of dysbiosis on protein expression levels in mouse liver and kidney by quantitative proteomic analysis, focusing in particular on drug-metabolizing enzymes and transporters in order to investigate the potential impact of dysbiosis on drug pharmacokinetics. Germ-free (GF) mice and antibiotics-treated mice were used as dysbiosis models. Expression levels of 825 and 357 proteins were significantly changed in liver and kidney, respectively, of GF mice (vs. specific-pathogen-free mice), while 306 and 178 proteins, respectively, were changed in antibiotics-treated mice (vs. vehicle controls). Among them, 52 and 16 drug-metabolizing enzyme and transporter proteins were significantly changed in liver and kidney, respectively, of GF mice, while 25 and 8, respectively were changed in antibiotics-treated mice. Expression of mitochondrial proteins was also changed in liver and kidney of both model mice. In GF mice, Oatp1a1 was decreased in both liver and kidney, while Sult1a1 and two Cyp enzymes were increased and Gstp1, four Cyp enzymes, three Ces enzymes, Bcrp1 and Oct1 were decreased in liver. In antibiotics-treated mice, Cyp51a1 was increased and three Cyp enzymes, Bcrp1 and Bsep were decreased in liver. Notably, expression of Cyp2b10 and Cyp3a11 was greatly decreased in liver of both models. Cyp2b activity in liver microsomal fraction was also decreased. Our results indicate that dysbiosis changes protein expression of multiple drug-metabolizing enzymes and transporters in liver and kidney, and may alter pharmacokinetics in the host.

KEYWORDS: antibiotics, drug-metabolizing enzyme, intestinal flora, quantitative proteomics, targeted proteomics, transporter 2 ACS Paragon Plus Environment

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INTRODUCTION Dysbiosis, which is an alteration in the quality or quantity of intestinal flora, influences host physiology, and is associated with various diseases, including type 2 diabetes mellitus, autism and inflammatory bowel disease.1–4 Antibiotic administration causes dysbiosis, and even a shortterm exposure may have a long-term impact on intestinal flora.5–7 This is potentially important, because antibiotics are widely used for treatment of bacterial infection, as well as to prevent infection during surgery. Further, they are often prescribed for patients with acute respiratory infection (even though this is mainly caused by viruses). Indeed, the proportion of antibiotic prescriptions for acute respiratory infection patients was 69.2% in 2012 in the United States,8 and 60% in 2005 in Japan.9 Interestingly, it was reported that mRNA and protein expression levels and activity of Cyp3a, a metabolizing enzyme, were decreased in liver of germ-free (GF) mice compared to specific-pathogen-free (SPF) mice, though there was no significant difference in the small intestine.10 These results suggest that intestinal dysbiosis can change the pharmacokinetics by altering drug metabolism. Since antibiotics are often administered together with other drugs, it is important to investigate whether, and to what extent, intestinal dysbiosis induced by antibiotics impacts on drug-drug interactions and the efficacy of co-administered drugs. Drugs are eliminated from the blood mainly via metabolism in liver and excretion from kidney. Cytochrome P450 (CYP) isoforms have a central role in oxidative biotransformation,11 and carboxylesterases (CES) catalyze the hydrolysis of various ester-containing drugs and prodrugs.12 UDP-glucuronosyltransferase (UGT),

glutathione S-transferase (GST) and

sulfotransferase (SULT) mediate glucuronidation, sulfation and glutathione conjugation, respectively. 3'-Phosphoadenosine 5'-phosphosulfate synthase (PAPSS) catalyzes the generation of PAPS, which is a sulfate donor required for all SULTs.13 Solute carrier (SLC) transporters and 3 ACS Paragon Plus Environment


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ATP-binding cassette (ABC) transporters generally function as uptake and efflux transporters, respectively, and influence the distribution and excretion of drugs in hepatocytes and proximal tubule cells of kidney.14 In addition to changes of Cyp3a, previous studies have found increase of Cyp2b9 and decrease of Oatp1a4, Oct1 and Mrp3 at the mRNA level in liver of GF mice, and increase of Sult1a1, Sult1c1 and Sult1c2 at the protein level in liver of GF rat.10,15,16 A recent comprehensive RNAseq quantification study also found that the mRNA expression levels of many drug-metabolizing enzymes and transporters were altered in the liver of GF mice.17 These results are consistent with the idea that dysbiosis affects the expression and function of multiple drug-metabolizing enzymes and transporters in the liver. In the kidney, uremic toxins, such as indoxyl sulfate and hippurate, are generated by gut microbiota, and dysbiosis resulting from treatment with lubiprostone (a medicine for constipation) decreased uremic toxins and ameliorated the progression of chronic kidney disease in mice.18 Various drug-metabolizing enzymes and transporters are expressed in the kidney, but so far, there is no information about how they are affected by intestinal dysbiosis. Therefore, detailed investigation of changes in the expression levels of drug-metabolizing enzymes and transporters in response to dysbiosis is important for understanding the influence of intestinal flora on host pharmacokinetics and the likelihood of interaction when other drugs are co-administered with antibiotics. The purpose of the present study was to comprehensively clarify changes in protein expression levels, especially of drug-metabolizing enzymes and transporters, in liver and kidney of dysbiotic mice by means of focused and targeted combined quantitative proteomic analysis. We chose GF mice, which have no intestinal bacteria over a prolonged period from birth, as a model of longterm dysbiosis and we used mice treated with antibiotics for 5 days as a short-term model. 4 ACS Paragon Plus Environment

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MATERIALS AND METHODS Materials Livers and kidneys

of ten-week-old male GF (Tsl:C57BL/6NCr[GF]) and SPF

(C57BL/6NCrSlc) mice were purchased from Sankyo Labo Service (Tokyo, Japan); sterility of the GF mice had been confirmed by the supplier. Vancomycin hydrochloride, polymyxin B sulfate and lysyl endopeptidase were purchased from Wako Pure Chemical Industries (Osaka, Japan). QIAamp Fast DNA Stool Mini Kit was purchased from Qiagen (Hilden, Germany). Taq DNA polymerase containing 10x Standard buffer (Taq) and dNTPs was purchased from BioAcademia (Osaka, Japan) and PCR primers were synthesized at Fasmac (Kanagawa, Japan). Plasma Membrane Protein Extraction Kit was purchased from BioVision (Milpitas, CA). Pierce BCA Protein Assay Kit was purchased from Thermo Fisher Scientific (Waltham, MA). Sequencing-grade modified trypsin (frozen) was purchased from Promega (Madison, WI). Isotope-labeled peptides were synthesized by Sigma-Aldrich (St. Louis, MO) or Thermoelectron (Sedanstr, Germany). NADPH Regenerating System Solution A and NADPH Regenerating System Solution B were purchased from Corning (Corning, NY). Benzyloxyresorufin (7benzyloxyresorufin) was purchased from Anaspec (Fremont, CA). Resorufin pentyl ether (7pentoxyresorufin) was purchased from Santa Cruz Biotechnology (Dallas, TX). Resorufin was purchased from Sigma-Aldrich. Other reagents were commercially available products of analytical or reagent grade.



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Treatment with Antibiotics Ten-week-old C57BL/6NJcl male mice (CLEA Japan, Tokyo, Japan) were housed individually with free access to food (CE-2, CLEA Japan) and water. Vancomycin hydrochloride (500 mg/L) and polymyxin B sulfate (100 mg/L) were added to the drinking water for 5 days. At the end of treatment, the livers and kidneys were collected (without food deprivation) and frozen using liquid nitrogen for determination of protein expression levels and Cyp2b activity. The feces were also collected immediately before (pre-administration) and at 1 day, 3 days and 5 days after administration to confirm the reduction of intestinal bacteria. Livers, kidneys and feces were collected from mice not given antibiotics as a vehicle control. All animal experiments were approved by the Institutional Animal Care and Use Committee in Kumamoto University, and were performed in accordance with the regulations for animal experiments in Kumamoto University.

Quantification of Total Bacteria by PCR Targeting 16S rRNA Gene DNA was extracted from 200 mg of frozen feces with the QIAamp Fast DNA Stool Mini Kit. DNA extraction was performed according to the manufacturer's protocol with slight modifications. In the present study, homogenization of stool samples was conducted using a PowerMasher II with BioMasher II (Nippi, Tokyo, Japan) instead of a vortex mixer to increase the recovery of DNA. The yield and purity of DNA were confirmed by measuring the absorbance at 260 and 280 nm using an Eppendorf BioSpectrometer basic (Eppendorf, Hamburg, Germany). The extracted DNA solution was diluted 100-fold with water, and diluted DNA solutions from pre-administration feces were further diluted to 50%, 25% and 10% as 6 ACS Paragon Plus Environment

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quantitative references. Amplification of 16S rRNA gene from total bacteria in mouse feces was conducted with primers Eub338F (5'-ACTCCTACGGGAGGCAGCAG-3') and Eub518R (5'ATTACCGCGGCTGCTGG-3').19 Each PCR reaction mixture (20 µL total volume) consisted of 0.1 µL Taq DNA polymerase (5 unit/µL), 1 µL 10x Standard buffer (Taq), 1.6 µL dNTPs (each 2.5 mM), 1 µL Eub338F primer (10 µM), 1 µL Eub518R primer (10 µM), 4 µL diluted DNA solution and water. The PCR reaction was performed with a C1000 Thermal Cycler (Bio-Rad, Hercules, CA) using the following parameters: initial denaturation at 95°C for 2 min, followed by 22 cycles of denaturation at 95°C for 30 s, annealing at 50°C for 30 s, elongation at 72°C for 1 min, and a final elongation at 72°C for 3 min. The PCR products were detected by agarose gel electrophoresis (2% agarose gel contained ethidium bromide) with UV transillumination using an Omega Lum G Imaging System (Gel Company, San Francisco, CA). Intensities of PCR product bands were quantified using Image J software (National Institutes of Health, Bethesda, MD) (Supplemental Figure S1).

Tissue Fractionation For proteomic analysis, cytosol, crude membrane and plasma membrane fractions were prepared from 50 mg of minced liver and kidney using the Plasma Membrane Protein Extraction Kit. The fractionation was performed according to the manufacturer's protocol with slight modifications, i.e., purification by centrifugation at 700 g after the homogenization step was conducted twice to increase the purity of the fractions. For Cyp2b enzyme activity determination, microsomal fraction was prepared from 250 mg of minced liver. The minced liver was homogenized in 1 mL 1.15% KCl solution using a Micro Smash MS-100R (Tomy Seiko, Tokyo,



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Japan) under cooling. The obtained suspension was centrifuged at 9,000 g for 20 min at 4°C and the supernatant was centrifuged at 105,000 g for 60 min at 4°C. The resulting precipitate was resuspended in suspension buffer (0.1 mM EDTA, 0.25 M sucrose, 10 mM Tris-HCl, pH 7.4). Protein concentrations of fraction aliquots were measured using the Pierce BCA Protein Assay Kit, with bovine serum albumin as the standard.

Protein Quantification Analysis Peptide sample preparation and proteomic analysis were conducted according to the method and under the LC−MS/MS conditions described in previous reports, with slight modifications.20– 22

The fractionated samples were denatured and solubilized with 12 mM sodium deoxycholate,

12 mM N-lauroylsarcosinate, and 100 mM Tris-HCl (pH 9.0). Then, the samples were reduced with 10 mM dithiothreitol, alkylated with 55 mM iodoacetamide, diluted 5-fold with 50 mM ammonium bicarbonate, and digested with lysyl endopeptidase at room temperature for 3 h, followed by sequence-grade modified trypsin at 37°C for 16 h. For targeted quantitative proteomics, stable isotope-labeled internal standard peptides were spiked into the samples after trypsin digestion. The samples were desalted and dissolved in 0.1% trifluoroacetic acid for LC−MS analysis. Protein expression levels were quantified by detection of specific peptides from the protein with sequential window acquisition of all theoretical fragment-ion spectra (SWATH) for focused quantitative proteomics,23 or with high-resolution multiple reaction monitoring (HR-MRM) for targeted quantitative proteomics.24 In focused quantitative proteomics, the MS/MS data from information-dependent acquisition using a peptide aliquot of each group was analyzed by 8 ACS Paragon Plus Environment

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ProteinPilot Software version 4.5 (Sciex, Framingham, MA) with the Paragon algorithm and Uniprot mouse proteome database for protein identification.25 Targeted peptide peaks were extracted from the SWATH data by PeakView Software version 2.1 (Sciex) using the identified protein data from ProteinPilot, and the sum of the area values of specific peptide peaks from each protein was calculated as the protein expression level. In targeted quantitative proteomics, product ion peaks from each targeted peptide and the internal standard peptide corresponding to the targeted peptide were extracted from the HR-MRM data and the peak area ratio of targeted peptide to internal standard peptide at each product ion was calculated by Skyline version 3.1 (MacCoss Laboratory, University of Washington, Seattle, WA).26 The protein expression level was determined as the average value of the peak ratios from 3 or 4 product ions. The transition information for targeted quantitative proteomics (HR-MRM measurement) is shown in Supplemental Table S1.

Functional Annotation Clustering and Enrichment Analysis DAVID (Database for Annotation, Visualization and Integrated Discovery) Bioinformatics Resources version 6.7 was used for functional annotation clustering and enrichment analysis.27 The analysis targeted proteins with significantly changed expression levels in either GF or antibiotics-treated mice in the focused quantitative proteomics (p < 0.05), and identified enrichment terms in each category (Biological process (GOTERM_BP_FAT), Cellular component (GOTERM_CC_FAT) or Molecular function (GOTERM_MF_FAT)) using the Uniprot accession numbers of the proteins obtained from the PeakView data.



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Cyp2b Enzyme Activity Determination Benzyloxyresorufin

(for

O-dealkylation

of

7-benzyloxyresorufin

(BROD))

and

pentoxyresorufin (for O-dealkylation of 7-pentoxyresorufin (PROD)) were used as selective substrates for mouse Cyp2b.28,29 Liver microsomal fractions (75 µg of protein) were preincubated in 25 mM potassium phosphate buffer (pH 7.4) containing benzyloxyresorufin (final concentration 0.025, 0.05, 0.1, 0.2, 0.4, 0.8, 1.6 or 3.2 µM) or pentoxyresorufin (final concentration 0.195, 0.391, 0.781, 1.56, 3.13, 6.25, 12.5 or 25 µM) at 37°C for 5 min, NADPH regenerating system (final concentrations: 1.3 mM NADP+, 3.3 mM glucose-6-phosphate, 0.4 U/ml glucose-6-phosphate dehydrogenase and 3.3 mM MgCl2) was added, and the reaction mixture (final volume of 0.3 ml) was incubated at 37°C for 7 min. Cooled methanol (0.15 ml) was added and the mixture was centrifuged at 16,000 g for 5 min at 4°C. The fluorescence (excitation at 572 nm and emission at 604 nm) of the supernatant (0.2 mL) was measured in duplicate using an Infinite M1000 (Tecan, Mannedorf, Switzerland), and the formation of resorufin was calculated with the aid of the prepared resorufin standard curve. The relationship between each substrate concentration and formation rate of resorufin was least-squares-fitted (weighted by 1/Y2) to an allosteric sigmoidal model, and kinetic parameters (Vmax: maximum velocity and Km: Michaelis constant) were calculated using GraphPad Prism version 6.0 (GraphPad software, San Diego, CA). The intrinsic clearance (CLint = Vmax/Km) was also calculated.


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Statistical analysis Numerical data were expressed as mean ± standard error of the mean. The statistical significance of differences was determined by Student’s t-test using Microsoft Excel version 14.0 (Microsoft, Redmond, WA).



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RESULTS Reduction of Intestinal Bacteria by Antibiotics To prepare the model mouse with a short-term decrease of intestinal bacteria, vancomycin (VCM) and polymyxin B (PLB), which are non-absorbable antibiotics active against Gram– positive bacteria and Gram–negative bacteria, respectively,30–33 were administered orally for 5 days to eliminate a broad spectrum of bacteria. Amounts of intestinal bacteria after antibiotics administration were evaluated by PCR assay of bacterial 16S ribosomal RNA gene in feces. In the antibiotics-treated mice (VCM+PLB mice), intestinal bacteria were decreased to less than about 25% of the pre-administration value after 5 days treatment (Figure 1A). There was no change in the amount of intestinal bacteria in the vehicle control mice after 5 days (Figure 1B). These VCM+PLB and control mice were used for the following experiments. The band intensities of PCR products are shown in Supplemental Figure S1; we confirmed that the band intensities of Day 0 DNA templates diluted to 50%, 25% and 10% decreased in a dilutiondependent manner.

Comprehensive Comparison of Protein Expression Levels in Liver and Kidney of Dysbiosis Model Mice by Focused Quantitative Proteomics. Protein expression levels in liver and kidney were comprehensively compared between GF and SPF mice, and between VCM+PLB and vehicle control mice by means of focused quantitative proteomics. Focused quantitative proteomics analyzes subcellular fractions of biological samples; this offers several advantages, such as greater sensitivity for proteins concentrated in


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these fractions, and measurement of protein levels at the site(s) where the proteins function. In the present study, liver and kidney were fractionated to cytosol, crude membrane fraction (containing all membrane components except for nuclear membrane) and plasma membrane fraction. The proteins with significantly changed expression levels (p < 0.05) in GF mice (vs. SPF) and in VCM+PLB mice (vs. vehicle control) are listed in Supplemental Tables S2 and S3. In GF mice, around 1600 proteins were identified, and among them, 825 proteins and 357 proteins showed significant changes of expression in liver and kidney, respectively (p < 0.05 vs. SPF mice) (Table 1). Of these proteins showing changed expression, 52 drug-metabolizing enzyme and transporter proteins were significantly changed in liver and 16 in kidney. In VCM+PLB mice, about 1900 proteins were identified, and among them, 306 proteins and 178 proteins showed significant changes of expression in liver and kidney, respectively (p < 0.05 vs vehicle control) (Table 1). Of these proteins showing changed expression, 25 drug-metabolizing enzyme and transporter proteins were significantly changed in the liver and 8 in the kidney.

Functional Annotation Clustering and Enrichment Analysis of Proteins Changed in Dysbiosis Model Mice. To investigate the effects of intestinal flora on host physiological functions, we performed functional annotation clustering and enrichment analysis using DAVID (Database for Annotation, Visualization and Integrated Discovery) bioinformatics resources for the proteins that were significantly changed (p < 0.05) in either GF or VCM+PLB mice. As shown in Table 2, in the category of biological process, proteins involved in ‘oxidation reduction’ were enriched in liver and kidney of both dysbiosis models. This term includes cytochrome P450 proteins related to 13 ACS Paragon Plus Environment


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drug metabolism. The terms ‘generation of precursor metabolites and energy’ and ‘cofactor or coenzyme binding’ were also enriched in the categories of biological process and molecular function, respectively, except in liver of VCM+PLB mice. Proteins categorized under ‘oxidation reduction’ and ‘generation of precursor metabolites and energy’ are involved in mitochondrial functions,34 and we found that terms related to mitochondria in the category of cellular component were also enriched in liver and kidney of both models. Therefore, significant changes of many proteins related to mitochondria are seen in dysbiosis model mice. Interestingly, in liver of GF and VCM+PLB mice and kidney of GF mice, more than half of the identified proteins in most terms were significantly increased, whereas in kidney of VCM+PLB mice, more than half of the identified proteins in all terms were significantly decreased.

Changes of Protein Expression Levels of Drug-metabolizing Enzymes and Transporters in Dysbiosis Model Mice, Determined by Targeted Quantitative Proteomics. Drug-metabolizing enzyme and transporter proteins whose expression levels were changed by more than 2-fold or less than 0.5-fold (p < 0.05), as determined by focused quantitative proteomics, were selected for more accurate targeted quantitative proteomics. The expression levels of selected proteins were quantified by spiking stable isotope-labeled internal standard peptides in the relevant fraction, such as cytosolic fraction for Sult and Gst, microsomal fraction for Cyp and Ces, and plasma membrane fraction for Abc and Slc (Slco and Slc22 families) transporters. Figure 2 shows drug-metabolizing enzyme and transporter proteins whose expression was significantly changed by more than 2-fold or less than 0.5-fold with focused


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quantitative proteomics in each GF or VCM+PLB mice. Data for all quantified proteins selected for targeted quantitative proteomics are included in Supplemental Figure S2. Gapdh for cytosolic fraction and Na+/K+-ATPase for crude and plasma membrane fractions were also quantitated as housekeeping proteins,35,36 and their changes ranged from 0.788-fold to 1.53-fold in GF and VCM+PLB mice (Figures 2A and 2B). The expression levels of Na+/K+ATPase in crude and plasma membrane fractions of model mice were not significantly different from those in the controls. The expression level of Gapdh was significantly altered (0.842-fold) in liver cytosolic fraction of GF mice, but this change was less than the changes of the drugmetabolizing enzyme and transporter proteins selected for quantification. These results suggest that the variance in subcellular fractions was sufficiently small to allow valid comparison of the expression levels of the selected proteins. In liver of GF mice, protein expression levels of Cyp2b10 and Cyp3a11 were decreased to 0.0404- and 0.172-fold, respectively, compared to those in SPF mice (Figure 2A). Oatp1a1 was decreased to below 0.5-fold in plasma membrane fraction of both liver and kidney of GF mice. Other than those proteins, Gstp1, two Cyp enzymes, three Ces enzymes, Bcrp1 and Oct1 were decreased and Sult1a1 and two Cyp enzymes were increased in liver of GF mice, and Cyp2a4 was increased in kidney of GF mice. In liver of VCM+PLB mice, protein expression levels of Cyp3a11, Cyp2b10 and Bcrp1 were decreased, as also seen in GF mice (Figure 2B). Cyp3a11 and Bcrp1 were decreased to 0.116and 0.494-fold, which are similar to the changes in GF mice (0.172-fold and 0.435-fold), respectively. Cyp2b10 was decreased to 0.445-fold, which was less than the decrease in GF mice



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(0.0404-fold). Cyp3a25 and Bsep were decreased, and Cyp51a1 was increased in liver of VCM+PLB mice.

Decrease of Cyp2b Activity in Liver Microsomal Fraction of Dysbiosis Model Mice. Cyp2b10 exhibited the greatest protein decrease among drug-metabolizing enzymes in liver of GF mice (0.0404-fold) and was also decreased 0.445-fold in VCM+PLB mice. To confirm this change at the functional level, we examined whether Cyp2b activity is reduced in liver microsomal fraction by using two Cyp2b-selective substrates, benzyloxyresorufin and pentoxyresorufin.28,29 In GF mice, Cyp2b activities were attenuated at all concentrations of the two substrates, compared to SPF mice (Figures 3A and 3B). The Vmax values were significantly decreased to 0.119- and 0.171-fold, and the CLint values were significantly decreased to 0.183and 0.194-fold for benzyloxyresorufin and pentoxyresorufin, respectively (Table 3). The Km value of pentoxyresorufin was not significantly changed, while that of benzyloxyresorufin was decreased 0.662-fold. In VCM+PLB mice, Cyp2b activities were also significantly decreased compared to vehicle control mice (Figures 3C and 3D). As shown in Table 3, Vmax was significantly decreased to 0.742-fold for benzyloxyresorufin, and non-significantly decreased to 0.790-fold for pentoxyresorufin. The CLint and Km values for both substrates were not significantly changed, even though the CLint value of benzyloxyresorufin was decreased to 0.790-fold.


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DISCUSSION In the present study, we comprehensively compared protein expression levels in liver and kidney of GF mice and VCM+PLB mice to those in SPF and vehicle control mice, respectively, by means of focused and targeted combined quantitative proteomics. Notably, the protein expression levels of Cyp2b10, Cyp3a11 and Bcrp1 were decreased to less than 50% in liver of both dysbiosis models. This suggests that alterations of intestinal flora markedly influence the protein expression of these molecules in liver in both models. As shown in Supplemental Figure S2, the change profile of drug-metabolizing enzymes and transporters in liver shows a similar tendency in both models. This may imply that the changes of protein expression levels in VCM+PLB mice were mainly caused by the antibiotics-induced reduction of intestinal bacteria. The degrees of change were greater in GF mice, with a few exceptions, possibly due to the much longer period of loss of intestinal bacteria. However, Cyp3a11, Cyp3a25, Cyp51a1 and Bsep showed greater changes in the liver of VCM+PLB mice than in GF mice. The reason for this is unknown, but might include a direct effect of the antibiotics and/or indirect effects. The protein expression levels of Cyp2b10 in the liver were decreased to 0.0404 and 0.445-fold in GF mice (vs. SPF) and VCM+PLB mice (vs. vehicle control), respectively (Figures 2A and 2B), and the Cyp2b activities in liver microsomal fractions were also decreased (Figure 3 and Table 3). CYP2B6 is a human homolog of Cyp2b10 and is thought to be involved in the metabolism of approximately 25% of therapeutic drugs.37,11 CYP2B6*6 is a clinically important, high-frequency haplotype with altered function; it has been reported that the CLint values were decreased to 17% (formation of 8-hydroxyefavirenz) and 3% (formation of 4-hydroxybupropion) in liver microsomal samples with CYP2B6*6/*6 genotype compared to CYP2B6*1/*1 genotype (wild type).38 In this study, the CLint values of benzyloxyresorufin and pentoxyresorufin due to 17 ACS Paragon Plus Environment


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Cyp2b in liver microsomes of GF mice were decreased to 18.3% and 19.4%, respectively (Table 3). These values are comparable with those in the case of CYP2B6*6/*6 genotype. Therefore, dysbiosis, especially long-term reduction of intestinal bacteria, may decrease CYP2B6 activity in human liver sufficiently to impact on drug metabolism. It should be noted that CYP2B6 exhibits more than 100-fold variability in expression in human liver microsomes,39 and notable interindividual differences in metabolic activities towards cyclophosphamide, efavirenz and bupropion have been reported even in subjects with the same genotype.38,40 Our results indicate that differences of intestinal flora may contribute in part to the inter-individual variability of CYP2B6 activity. The difference in Cyp2b activity between SPF and vehicle control mice might be due to the difference in substrains and/or differences in rearing environment, because these mice were purchased from different suppliers. Previous studies showed that mRNA expression of Cyp3a11 in mouse liver was decreased by antibiotic (ciprofloxacin) administration for 5 days, and mRNA expression of Cyp3a subfamily members (Cyp3a11, Cyp3a16, Cyp3a25, Cyp3a41 and Cyp3a44) was decreased in liver of GF mice.41,10 The present results indicated that short-term antibiotic administration decreases protein expression of Cyp3a11 in liver microsomal fraction (Figure 2B). Therefore, dysbiosis due to short-term antibiotic administration may also decreases the function of CYP3A4, which is the human homolog of Cyp3a11,42 in human liver. Since it has been reported that administration of clindamycin for 7 days affects the intestinal flora for up to two years,43 even short-term antibiotic administration may cause prolonged changes in drug pharmacokinetics. Over half of drugs on the market are metabolized by either CYP2B6 or CYP3A4,11 so it is possible that dysbiosis of intestinal flora could have a dramatic impact on drug metabolism in liver.


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Among drug transporters, the protein expression levels of Bcrp1 in the liver were decreased 0.435- and 0.494-fold in GF mice (vs. SPF mice) and VCM+PLB mice (vs. vehicle control), respectively (Figures 2A and 2B). BCRP is expressed on the canalicular membrane of hepatocytes and facilitates biliary excretion of drugs.44,45 Many anticancer drugs such as mitoxantrone and topotecan are BCRP substrates, and those anticancer drugs are often used in combination with antibiotics to treat infections associated with myelosuppression, a side effect of these anticancer drugs.45,46 Therefore, dysbiosis caused by antibiotic administration may alter the pharmacokinetics of anticancer drugs via a reduction in the protein expression level of BCRP. Changes of the mRNA levels of drug-metabolizing enzymes and transporters in liver of GF C57BL6 mice (the same strain used in the present study) were comprehensively examined in a recent study.17 Among the changed molecules in both studies, the expression levels of 10 molecules, i.e., Cyp2a5, Cyp2b10, Cyp3a11, Ugt2b35, Ces2a, Ces3b, Sult1a1, Sult1d1, Gstm3 and Gstp1, were changed in the same direction at both the protein and mRNA levels (Supplemental Table S6). In contrast, Cyp1a2 was decreased at the protein level, but increased at the mRNA level. A low correlation between mRNA and protein expression levels of CYP1A2 has been reported in human liver microsomes.47 Therefore, post-transcriptional regulation may significantly influence the hepatic expression of Cyp1a2 protein under dysbiosis. In kidney, the protein expression level of Oatp1a1 was decreased 0.422-fold in GF mice (Figure 2A). Although the human homolog of Oatp1a1 is still unclear, OATP4C1 is the only human OATP family member predominantly expressed in kidney, and it plays a role in renal excretion of drugs such as digoxin.48 Drug interaction between digoxin and macrolide antibiotics such as clarithromycin is known to cause an increase of digoxin blood concentration, which may be due to inhibition of MDR1 by macrolide antibiotic or to reduced digoxin-metabolizing 19 ACS Paragon Plus Environment


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capacity of bacteria in the intestine.49–52 If the protein expression level of OATP4C1 in human kidney is decreased by dysbiosis, like that of Oatp1a1 in GF mice, intestinal dysbiosis could cause an increase of blood concentration of digoxin due to a reduction of renal excretion. As digoxin has a narrow therapeutic range,50 further study would be desirable to clarify the influence of dysbiosis resulting from antibiotic administration on digoxin pharmacokinetics. It has been reported that administration of lithocholic acid (LCA) to GF mice increased Cyp3a11 mRNA expression level in liver, and ciprofloxacin administration decreased Cyp3a11 mRNA expression level and LCA exposure in liver.41 LCA is a secondary bile acid produced by intestinal bacteria,53 and is an activator of pregnane X receptor (PXR) and farnesoid X receptor (FXR), which are involved in positive regulation of Cyp3A4/3a11 expression.54–56 It has been reported that CYP2B6, CYP2C9, Ces2a and Ces2c expressions are regulated positively by PXR, and BSEP is regulated positively by FXR.57–60 On the other hand, Cyp51a1, which is involved in the cholesterol biosynthetic pathway as a sterol 14α-demethylase, is regulated negatively by FXR.61,62 Therefore, suppression of Cyp3a11, Cyp2b10, Cyp2c29, Ces2a, Ces2c and Bsep and induction of Cyp51a1 may result from the reduction of LCA due to dysbiosis (Figures 2A and 2B). Our functional annotation clustering and enrichment analysis revealed that proteins associated with mitochondria were changed in GF and VCM+PLB mice (Table 2). Earlier studies have suggested a relationship between intestinal flora and glucose metabolism. Colonization of microbiota in GF mice produced an insulin-resistant state within 14 days.63 Norfloxacin and ampicillin treatment for 14 days enhanced glucose tolerance in diet-induced obese mice and ob/ob mice.64 Ampicillin, neomycin and metronidazole administration for 8 weeks to high-fatfed mice improved insulin signaling in liver and glucose tolerance.65 It has also been reported 20 ACS Paragon Plus Environment

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that mitochondrial biogenesis is decreased in liver of insulin-resistant mice.66 Here, we found that proteins relating to mitochondria tended to be induced in liver of GF and VCM+PLB mice. Furthermore, mitochondrial fission 1 protein (Fis1) and mitofusin-1 (Mfn1), which are involved in mitochondrial biogenesis,66 were increased 1.28-fold (p = 0.0120) and 1.64-fold (p = 0.0516) in GF mice and 1.15-fold (p = 0.0563) and 1.30-fold (p = 0.136) in VCM+PLB mice, respectively, in liver crude membrane fractions by focused quantitative proteomic analysis (data not shown, except for Fis1 in GF mice (Supplemental Table S2)). Therefore, it seems likely that mitochondrial biogenesis is induced in liver of dysbiosis model mice through insulin signaling. In the kidney, the expression levels of proteins associated with mitochondria tended to be increased or decreased in GF or VCM+PLB mice, respectively. However, the reason for the apparent difference is unclear, though alterations of intestinal flora may affect kidney function via changes in the expression levels of mitochondrial proteins. Indeed, it was reported that Staphyloccocus aureus sepsis induced renal mitochondrial biogenesis in mice.67 In conclusion, our results indicate that loss or decrease of intestinal flora significantly changes the protein expression levels of multiple proteins, including drug-metabolizing enzymes and transporters, in liver and kidney. Therefore, it will be important in the future to examine whether dysbiosis induced by antibiotics administration alters the pharmacokinetics of co-administered drugs. Further study is also needed to clarify the molecular mechanisms through which dysbiosis influences the regulation of drug-metabolizing enzymes and transporters. Our results suggest that dysbiosis could contribute to drug-drug interactions and inter-individual variation of pharmacokinetics.



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ACKNOWLEDGMENT The authors would like to thank T. Terasaki for providing set of labeled peptides for targeted proteomics. This study was supported in part by Grant-in-Aids for Scientific Research from the Japanese Society for the Promotion of Science, AMED-CREST from Japan Agency for Medical Research and Development, and the Funding Program for Next Generation World-Leading Researchers by the Cabinet Office, Government of Japan.


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ASSOCIATED CONTENT Supporting Information. Figure S1 shows intensities of PCR product bands from bacterial 16S rRNA genes in feces of mice treated with antibiotics or vehicle; Figure S2 compares the changes of expression of all proteins selected for targeted quantitative proteomics in GF and VCM+PLB mice; Table S1 shows transition information for HR-MRM measurements; Table S2 lists proteins with significantly different expression levels in GF and SPF mice, as determined by focused quantitative proteomics; Table S3 lists proteins with significantly different expression levels in VCM+PLB and vehicle control mice, as determined by focused quantitative proteomics; Table S4 shows relative protein expression levels in GF mice compared to SPF mice, as determined by targeted quantitative proteomics; Table S5 shows relative protein expression levels in VCM+PLB mice compared to vehicle control mice, as determined by targeted quantitative proteomics; Table S6 compares the changes in expression of drug-metabolizing enzymes and transporters in liver of GF C57BL6 mice at the protein level (found in the present study) and mRNA level (reported by Selwyn et al.). This material is available free of charge via the Internet at http://pubs.acs.org.

AUTHOR INFORMATION Corresponding Author *Department of Pharmaceutical Microbiology, Faculty of Life Sciences, Kumamoto University, 5-1 Oe-honmachi, Chuo-ku, Kumamoto 862-0973, Japan. Tel: +81-96-371-4323. Fax: +81-96371-4329. E-mail: [email protected].



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Notes Sumio Ohtsuki is a full professor at Kumamoto University and is also a director of Proteomedix Frontiers. Takuya Kuno is an employee of Otsuka Pharmaceutical Co., Ltd. This study was not supported by either of the companies, and their positions at the companies did not influence the design of the study, the collection of the data, the analysis or interpretation of the data, the decision to submit the manuscript for publication, or the writing of the manuscript and did not present any financial conflicts. The other authors declare no competing interests.

ABBREVIATIONS GF, germ-free; SPF, specific pathogen-free; CYP, cytochrome P450; CES, carboxylesterase; UGT, UDP-glucuronosyltransferase; GST, glutathione S-transferase; SULT, sulfotransferase; PAPSS, 3'-phosphoadenosine 5'-phosphosulfate synthase; SLC transporter, solute carrier transporter; ABC transporter, ATP-binding cassette transporter; Oatp, organic anion transport polypeptide; Oct, organic cation transporter; Mrp, multidrug resistance-associated protein; VCM, vancomycin; PLB, polymyxin B; LC−MS/MS, liquid chromatography−tandem mass spectrometry; SWATH, sequential window acquisition of all theoretical fragment-ion spectra; HR-MRM, multiple reaction monitoring under high-resolution; BROD, O-dealkylation of 7benzyloxyresorufin; PROD, O-dealkylation of 7-pentoxyresorufin; Gapdh, glyceraldehyde-3phosphate dehydrogenase; Bcrp, breast cancer resistance protein; Bsep, bile salt export pump; MDR, multidrug resistance protein; LCA, lithocholic acid; PXR, pregnane X receptor; FXR, farnesoid X receptor; Fis1, mitochondrial fission 1 protein; Mfn1, mitofusin-1


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Figure legends Figure 1. Decrease of bacterial content in feces after antibiotics administration. Total bacterial contents in feces collected from mice treated with antibiotics (VCM+PLB) (A) or vehicle (Vehicle control) (B) for 5 days were analyzed by PCR assay of 16S rRNA gene targeting all bacteria. The amounts of templates extracted from a fixed amount of feces (200 mg) were used for the PCR reaction. The feces were collected pre-administration (Day 0), and at 1 day (Day 1), 3 day (Day 3) and 5 day (Day 5) after administration. In pre-administration feces, the PCR products amplified from DNA samples of Day 0 diluted to 50%, 25% and 10% were also analyzed as quantitative references.

Figure 2. Relative changes of protein expression levels of drug-metabolizing enzymes and transporters in dysbiosis model mice. Fold changes of protein expression levels in each tissue fraction in GF mice compared to those in SPF mice (A, n = 3) or those in VCM+PLB mice compared to those in vehicle control mice (B, n = 4) are presented as mean ± S.E.M.. *p < 0.05, **p < 0.01 and ***p < 0.001, significantly different from SPF mice or vehicle control mice by Student’s t-test.

Figure 3. Cyp2b activities in liver microsomes of dysbiosis model and control mice. The formation rates of resorufin from benzyloxyresorufin (A and C) or pentoxyresorufin (B and D) in liver microsome fraction were determined in GF mice (filled circle) and SPF mice (open circle) (A and B, n = 3) or VCM+PLB mice (filled diamond) and vehicle control mice (open 36 ACS Paragon Plus Environment

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diamond) (C and D, n = 4). Each point represents mean ± S.E.M.. Error bars are smaller than the symbols, where not shown. *p < 0.05, **p < 0.01 and ***p < 0.001, significantly different from SPF mice or vehicle control mice by Student’s t-test.



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Table 1. Numbers of identified proteins and proteins with significantly changed expression levels in dysbiosis model mice compared to controlsa

Dysbiosis model mice

Tissue

Liver

GF

Fraction

Number of proteins Drug-metabolizing enzymesb Identified proteins and transportersc >2-fold >2-fold All p

Effect of Intestinal Flora on Protein Expression of Drug-Metabolizing

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